Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/82912
Author(s): Luís Moreira Matias
Rafael Nunes
Michel Ferreira
João Mendes Moreira
João Gama
Title: On predicting a call center's workload: A discretization-based approach
Issue Date: 2014
Abstract: Agent scheduling in call centers is a major management problem as the optimal ratio between service quality and costs is hardly achieved. In the literature, regression and time series analysis methods have been used to address this problem by predicting the future arrival counts. In this paper, we propose to discretize these target variables into finite intervals. By reducing its domain length, the goal is to accurately mine the demand peaks as these are the main cause for abandoned calls. This was done by employing multi-class classification. This approach was tested on a real-world dataset acquired through a taxi dispatching call center. The results demonstrate that this framework can accurately reduce the number of abandoned calls, while maintaining a reasonable staff-based cost. © 2014 Springer International Publishing.
Subject: Inteligência artificial, Ciências da computação e da informação
Artificial intelligence, Computer and information sciences
Scientific areas: Ciências exactas e naturais::Ciências da computação e da informação
Natural sciences::Computer and information sciences
URI: https://repositorio-aberto.up.pt/handle/10216/82912
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FCUP - Artigo em Livro de Atas de Conferência Internacional
FEP - Artigo em Livro de Atas de Conferência Internacional
FEUP - Artigo em Livro de Atas de Conferência Internacional

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